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Diagnostic value of tumor blood flow and its histogram analysis obtained with pCASL to differentiate sinonasal malignant lymphoma from squamous cell carcinoma
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Diagnostic value of tumor blood flow and its histogram analysis obtained with pCASL to differentiate sinonasal malignant lymphoma from squamous cell carcinoma

Noriyuki Fujima, Hiroyuki Kameda, Akiko Tsukahara, Daisuke Yoshida, Tomohiro Sakashita, Akihiro Homma, Khin Khin Tha, Kohsuke Kudo, Hiroki Shirato 和 Fang-Hsin Chen
European journal of radiology, 卷.84(11), 頁碼.2187-2193
01/11/2015
PMID: 26277497
Web of Science ID: WOS:000363265600021

摘要

Malignant lymphoma Pseudo-continuous arterial spin labeling Squamous cell carcinoma Tumor blood flow
•The TBF value and its histogram obtained by pCASL can help differentiate SCC and ML.•The mean TBF in SCC patients was significantly higher than that of ML patients.•In the SCC patients, the histogram CV was significantly higher than the ML patients.•The combined use of the mean TBF and histogram CV provides high diagnostic accuracy. To investigate the diagnostic value of tumor blood flow (TBF) obtained with pseudo-continuous arterial spin labeling (pCASL) for the differentiation of squamous cell carcinoma (SCC) and malignant lymphoma (ML) in the nasal or sinonasal cavity. Thirty-three patients with SCC and 6 patients with ML in the nasal or sinonasal cavity were retrospectively analyzed. Quantitative TBF values were obtained using whole-tumor region of interest (ROI) from pCASL data. The histogram analysis of TBF values within the tumor ROI was also performed by calculating the coefficient of variation (CV), kurtosis, and skewness. The mean TBF value, histogram CV, kurtosis and skewness of the patients with SCC were compared with those of the ML patients. The diagnostic accuracy to differentiate SCC from ML was also calculated by receiver operating characteristic (ROC) curve analysis. In addition, multiple logistic regression models were also performed to determine their independent predictive value, and diagnostic accuracy with the combined use of these parameters. Between the SCC and ML groups, significant differences were observed in mean TBF, CV, and kurtosis, but not in skewness. In ROC curve analysis, the diagnostic accuracy values for the differentiation of SCC from ML in mean TBF, CV, and kurtosis were all 0.87, respectively. Multiple logistic regression models revealed TBF and CV were respectively independent predictive value. With the combination of these parameters, the diagnostic accuracy was elevated to 0.97. The TBF value and its histogram analysis obtained with pCASL can help differentiate SCC and ML.

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url
https://doi.org/10.1016/j.ejrad.2015.07.026檢視
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